燕山大学学报2017，Vol.41Issue(2)：183-188,6.DOI:10.3969/j.issn.1007-791X.2017.02.013
自适应贪婪搜索的人工蜂群算法
Adaptive greedy searching artificial bee colony algorithm
摘要
Abstract
Artificial bee colony (ABC) algorithm inspired by the foraging behaviour of the honey bees is one of the swarm intelligence based optimization techniques.Adaptive greedy search ABC (AGS-ABC) is a new version of ABC algorithm in order to enhance the exploitation performance of ABC,which models the behavior of onlooker bees more accurately.In the phase of onlooker bees,the search radius shrinks adaptively and the onlooker bees can search the same food source again after a successful search on the food source in order to make the best of successful search experience and diminish the blind search.Experiments on 10 benchmark functions show that AGS-ABC outperforms ABC and recently developed quick ABC(qABC) in terms of convergence accuracy and have less complexity compared to the two algorithms.关键词
人工蜂群算法/贪婪搜索/自适应策略/计算复杂度Key words
artificial bee colony/greedy search/adaptive strategy/computational complexity分类
信息技术与安全科学引用本文复制引用
杜振鑫,韩德志,曾亮..自适应贪婪搜索的人工蜂群算法[J].燕山大学学报,2017,41(2):183-188,6.基金项目
国家自然科学基金资助项目(61373028) （61373028）
